Physical process based erosion models like SWAT, WEPP etc. are very data demanding in both their amount of input variables and their temporal and spatial resolution requirements. On the other hand, less data demanding empirical based models are developed for a certain environmental set up and their applicability are restricted to the region where they are developed. Basically, landscape erosion risk modeling involves various environmental controlling parameters which are fuzzy in reality. When mapping erosion risk, the introduction of fuzzy sets instead of crisp sets to define classes will help to incorporate the degree of fuzziness within each class. The ability of fuzzy logic to describe and transform the knowledge in a descriptive human like manner in the form of simple rules using defined linguistic variables have provided a new direction to explore and develop a simple, efficient and well structured tool. This proposed research aims at developing a fuzzy based methodological framework to map the degree and magnitude of the interaction, between the changing patterns of various parameters that influence water induced land erosion processes and the influence of these changes on the rate of soil loss. The spatial distribution of the erosion potential (or the actual erosion risk, resp.) should be the result of the fuzzy modelling.